Excess alcohol consumption can cause liver disease and cancers. These harms can be prevented. Alcohol related-liver disease (ARLD) is one of the main causes of death and disease related to the digestive system. It is known that inequalities, such as deprivation level and ethnicity, exist and contribute to the burden of ARLD and deaths resulting from it. However, it is not well understood how inequalities influence ARLD and ARLD-related death.
The aim of this study is to develop a better understanding of the effect of ethnicity and deprivation on ARLD disease burden and deaths. This will allow us to explore the vulnerable groups who may be at increased risk, in order to prioritise prevention and early intervention – which may in turn reduce disease burden and ARLD-related deaths.
We will achieve this by:
1. describing the percentage of people with a diagnosis of ARLD by age group, sex, region, ethnic group and deprivation level, and by looking at how this has changed over the last decade;
2. describing the number of new cases of ARLD diagnosed each year, from 2009 to 2020, again by age group, sex, region, ethnic group and deprivation level;
3. comparing mortality (death) rates between people with ARLD and those without ARLD, and looking at any differences there may be in subgroups by age, sex, region, ethnic group and deprivation level;
4. exploring hospital admission rates in those with ARLD, by age, sex, region, ethnic group and deprivation level.
There is limited available data on the distribution of alcohol related-liver disease (ARLD) burden particularly in terms of deprivation and ethnic inequalities. We will conduct a descriptive study to allow us to develop a better understanding of the distribution of ARLD and mortality across the sociodemographic strata. This may highlight specific groups who are at increased risk of developing ARLD, supporting prevention and early intervention strategies.
Study objectives:
1. Calculate yearly ARLD prevalence 2009-2020 stratified by age, sex, region, ethnicity and socioeconomic deprivation.
2. Calculate annual ARLD incidence 2009-2020 stratified by age, sex, region, ethnicity and deprivation.
3. Compare mortality rates in individuals with and without ARLD by age, sex, region, ethnicity and deprivation.
4. Compare scheduled and unscheduled hospital admission rates in patients with ARLD by age group, sex, region, ethnicity and deprivation.
Study population: Patients aged 18 years and above registered at a practice contributing to CPRD Aurum.
Exposure: For objective 3, ARLD; for objective 4, exposures/risk factors of interest are age, sex, region, ethnicity and deprivation.
Outcomes: Mortality (objective 3) and hospital admissions (objective 4).
Study design and analysis:
1. Prevalence: yearly cross-sectional analyses (2009-2020).
2. Incidence: annual cohort studies (2009-2020).
3. Mortality: cohort study (2009-2020); Cox proportional-hazards regression model will be used to calculate unadjusted/adjusted hazard ratios.
4. Hospital admissions: cohort study (2009-2020); Poisson regression models will be used to calculate unadjusted/adjusted incidence rate ratios.
Recording of ARLD in primary care is likely to be incomplete. We will therefore explore 3 definitions of ARLD:
1. Definite ARLD: clinically coded ARLD;
2. Probable ARLD: clinically coded ARLD OR a non-specific liver disease clinical code* plus recorded alcohol misuse or high number of alcohol units;
3. Possible ARLD: clinically coded ARLD OR unspecified liver disease.*
*excluding liver disease due to other known causes such as viral hepatitis.
For part 1, yearly prevalence analysis, alcohol related-liver disease (ARLD) cases in the database on 1st January of year will be counted.
For part 2, annual incidence calculation, new ARLD cases over the period of one year will be counted, excluding any known previous ARLD cases.
For part 3, cohort study, outcome will be all-cause mortality (and cause-specific/ARLD-related mortality only in those with ARLD).
For part 4, cohort study, outcome will be scheduled and unscheduled hospital admissions (secondary outcome).
Nicola Adderley - Chief Investigator - University of Birmingham
Zhaonan Wang - Corresponding Applicant - University of Birmingham
Neeraj Bhala - Collaborator - University Hospitals Birmingham
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation